NSE) & Bombay Stock Exchange (BSE)
International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020 A Study on The Novel Coronavirus Pandemic (Covid 19) Impact on Major Sectoral Indices in National Stock Exchange (NSE) & Bombay Stock Exchange (BSE)
1Dr. S. SARAVANAN, 2R. VIDHYATHARAN Department of Management studies, Anna University, BIT Campus, Trichy, India.
ABSTRACT - The virus that has spooked the world’s markets and sparked fear of downturn worldwide has also destructed Indian stock market. Whether the Current market fall can be a best buying opportunity for investors. The world has suddenly become a different place in the last six months, with Coronavirus taking a host of nations by storm. Markets in the US, as well as India, were very strong for quite a while. The stock market fall, in the worldwide markets and India, is for the most part by virtue of Fear of the Unknown. What amount can the circumstance prolong, how viably will nations react in containing the pandemic, in how much time, and the degree of crippling impact this whole circumstance will emphasis on economic activity, demand and trade. The objective of this paper is to estimate the expected return of selected securities from major sectoral indices from NSE & BSE, and to compare their performances i.e. before and after the strike of novel coronavirus pandemic. The 5 different sectors listed in National Stock Exchange (NSE) like Nifty Auto, Nifty Energy, Nifty pharma, Nifty financial services, Nifty FMCG and Bombay Stock Exchange (BSE) like S&P BSE Auto, S&P BSE Energy, S&P BSE Power, S&P BSE Healthcare, S&P BSE FMCG, S&P BSE Bankex are taken into account and 5 securities from each sector is selected for calculating the expected return. The data is collected for the securities listed in NSE for the time frame of 6 months from 1st November 2019 to 30th April 2020 to estimate the expected return on the stock. The securities are ranked based on the CAPM expected return for the above specified period. The study further extended on the determining the Alpha(α) Beta(β) and coefficient of determination (R2) to find the variance in proportion of dependent variable to that of independent variable.
Key words: CAPM, Alpha, Beta, NSE, BSE, R square, Sectoral indices, Novel Coronavirus, Covid
I. INTRODUCTION caused due to Covid-19 on operations. Globally, stock markets are in a bear grip on concerns over the novel Coronaviruses are a huge group of infections that cause coronavirus, major industrial sectors like Chemical illness extending from the basic virus to increasingly Industry, Shipping Industry, Auto Industry, severe diseases and Severe Acute Respiratory Syndrome. Pharmaceuticals Industry, Textiles Industry, IT Industry, As the coronavirus (COVID-19) pandemic keeps on Tourism and Aviation had an impact of Covid-19. Banks frightening the global equity markets generally Asian and and financial institutions will be under immense pressure European markets enrolled enormous misfortunes over the as the fear of NPA, on the other side India's fuel demand in economic aftermath. Speculator notion in India is low to April 2020 as compared to the previous year fell nearly the point that regardless of moderately lower cases, Indian 46%, E-commerce platforms in India announced that it market has fared most exceedingly awful among global would stop sale of non-essential items in India so that it peers. Indian stock market has lost 26 % in terms of dollar can focus on essential needs. There is no doubt that Covid- between February 1 and April 9, contrasted and a fall of 20 19 will have a large impact on the Indian economy, The % and 14 % in the European and US markets. India is recovery of the underlying economy will be slow, and may opening up its economy and taking steps to return to take around 2 years for normalcy to come back across normalcy, The Reserve Bank of India slashed lending sectors. Everyone does predictions. It doesn’t cost rates, predicting India's GDP growth in 2020-2021 would anything and does no harm. Not in my line of work, Stock slow down due to the coronavirus lockdown. Major markets have a mind of their own, formed by the collective manufacturing companies in India have temporarily emotions and intelligence of millions. Stock markets are suspended operations and FMCG companies in the country frequently slanted and aren't the best pointers of the basic have significantly reduced operations and are focusing on economy. Stock markets will have a solid recuperation, not essentials. In India up to 53% of organizations have determined a specific measure of effect as shutdowns
162 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020 because of the essentials quality, yet because of worldwide the securities by their choice. The study liquidity. provides data concerning the performance of assorted stocks within the market in terms of risk India has dropped out from the rundown of the world's best and come with the assistance of CAPM. Whereas in case 10 stock markets as the covid-19 pandemic prompted a of automobile sector firms here, investors may choose defeat in worldwide values, desolating valuations Hieronymus Bosch 3.48% and Maruti Suzuki Ltd 5.31%. altogether this year. India's benchmark indices entered a Whereas in case of IT sector firms here, they bear market and India is no longer part of the $2-trillion can choose HCL Technologies (1.02%). Since the author market cap club, tumbling to the eleventh spot in the has select solely 2 sectors like IT and automobile alliance table with $1.57 trillion market cap. In January, Sectors, wherever the auto firms has performed higher and India was positioned 10 with a market cap of $2.16 trillion, has accumulated growth within the market when put and was in the seventh spot while in January 2019, with a next to that Sector has negative average returns. total market cap of $2.08 trillion. India tumbled out of the top 10 list at the end March 2020, when the benchmark Dr.S.Saravanan and R.Vidhyatharan, “A study on indices saw one of the biggest one-day decline, with the performance evaluation of different sectoral indices in Sensex losing 13.15%. March 2020 will be recorded in national stock exchange (2020)” examined that from the capital market history as an exceptional month. Stock past data they infer that NESTLEIND & BRITANNIA has markets in India post exceedingly terrible misfortunes the highest expected return of 4.9148% & 4.3745% ever. SENSEX fell over 4000 points and NIFTY over 1150 respectively from the selected securities. These two points, top 5 Nifty losers are financial sectors and slip securities represent the FMCG sector and have a high yield up to 5%. Markets dread as vulnerability wins and return as far as other sectors are concerned. And also markets the world over colliding with levels not witnessed indicates that FMCG sector has ranked further ahead when since the Global Financial Crisis of 2008. Following the compared to other sectors which have taken in to solid connection with the patterns and indices of the consideration for the above study. Apart from FMCG worldwide market as BSE Sensex and Nifty 50 fell by sectors, the energy sectors performs well and yield high 38%. The all out market top lost an amazing 27.31% from return. The banking sector has progressively number of the beginning of the year. Half of the Nifty 50 stocks, negative returns and has a low performance with that of barring financials, are trading at single digit valuations as different sectors which has been chosen for the Indian equity markets are almost 33% off record- examination. Though automobile sector and IT sectors significant levels they scaled in January. The Indian stock exhibits a moderate performance markets are much lower in percentage terms when Chintan A. Shah (2015) this examination was generally compared to the Asian and European markets, as certain about the Sharpe model gives precise number of securities sector, for example, hospitality, tourism and entertainment close by weightage for venture, while this is past the have been affected unfavourably and stocks of such domain of creative mind in CAPM model. They are organizations are down by over 40%. While the world has utilized the graphic research structure and optional seen numerous monetary crises previously, the last one information is utilized as a significant thing right now. being the worldwide downturn of 2008, the current CAPM model simply suggest different securities where coronavirus crises is not quite the same as the past financial pro can contribute anyway it doesn't give a fallout's. Drops in SENSEX and NIFTY are temporary, particular portfolio and weightage to interest in different and each dip provides investors with the opportunity to securities. Considering the examination of benefits of top enter the market and earn a higher return especially for 15 BSE securities from past years data using Sharpe those with long term horizon. Moreover, the higher the Model, a financial authority can place assets into following volatility, the higher odds of showing signs of better securities. HDFC Bank, ICICI Bank, HDFC, TATA returns. While these crisis are genuine and it impacts the Motors and TCS world economy, however truly, such emergency has not kept going long, as the world is skilful enough to think of Dr.Rupinder Katoch, january (2018) The Capital Asset answers and battle these difficulties. In spite of the way Pricing Model: An Empirical Test on Indian Stock Market that it's difficult to foresee the extent and effect of and the investigation finishes up blended reactions to the Coronavirus on the economy, however it is sure that the uses of CAPM in Indian Stock Market. The assessment markets will ricochet back soon the crisis gets over. started with the purpose of holding CAPM on Indian Stock Market viz. to test whether higher beta yields higher II. REVIEW OF LITERATURE expected return and the catch ascends to zero. The results Dr. S Poornima and Swathiga P, june(2017) the study is on of CAPM's estimates that higher risk (beta) is connected the relationship between risk and return analysis to select with a progressively huge degree of return. stocks on NSE capital quality valuation model this shows Dr.S.Saravanan and R.Vidhyatharan, Interpretation of the relation of risk and return causes the investor to select Stock Beta in national stock exchange, India (2020)
163 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020 examined that from the past data we can infer that YES a) The study covers only 25 listed securities from NSE & BANK has the highest beta value among all the securities BSE. listed in Nifty 50 and only 16 securities has beta value b) This study is limited to the CAPM return of 25 stocks greater than 1 and indicates the amount of risk and ability only. to fetch high potential return. And furthermore shows that c) Past 6 month data has been used for the calculation banking sector securities has a bigger impact in Nifty 50 and it has been divided into two equal time frames for by means for the beta value. As far as coefficient of estimating the return using CAPM. determination concern in explaining the size effect, the d) In the study, five major sectors have been chosen. The TATA STEEL has a highest proportion of the variance study covers only these 5 sectors based on NSE & that can be predicted from the corresponding market and BSE, five companies have been taken from each suggests that the model is good in explaining the size sector. effect among the other listed securities in the market. IV. DATA III. RESEARCH DESIGN Here, researcher has used Descriptive Research Design because in this research design the researcher has got very 3.1 PROBLEM DEFINITION: specific objectives and clear-cut data requirements. Daily To estimate the return and rank them based on their returns data for 25 securities from NSE & BSE are collected for a before and after the novel corona pandemic in their time frame of 6 months that is from November 1st 2019 to respective markets and to find the performance by 31st January 2020 (3 months) has been taken as duration comparing the same among the different sectoral indices in before bang of corona and from 1st February 2020 to April NSE & BSE. 30th 2020 (3 months) has been taken as duration after the bang of corona. Data collected is a secondary data and 3.2 NEED OF THE STUDY: been collected from the NSE & BSE websites respectively. a. To understand the impact level of the novel corona pandemic and its supremacy in Indian stock The selected securities from different sectoral indices exchanges (NSE & BSE) by comparing the (NSE & BSE): performances of the securities. b. To measure the change in performance for securities Table 4.1 selected securities from different sectoral in NSE & BSE i.e. before and after strike of corona. indices (NSE & BSE). c. To understand the level of significance for the S.no SYMBOL SECTOR (NSE) SECTOR (BSE) proportion of beta value for the same securities listed in both NSE & BSE. 1 BAJAJ-AUTO NIFTY AUTO S&P BSE AUTO d. To know the importance of beta value and how it influences the individual stock in the corresponding 2 EXIDEIND NIFTY AUTO S&P BSE AUTO market. e. To measure the variance in proportion of the 3 HEROMOTOCO NIFTY AUTO S&P BSE AUTO dependent variable to that of the independent variable in respective markets. 4 MARUTI NIFTY AUTO S&P BSE AUTO 3.3 OBJECTIVE OF THE STUDY: 5 MRF NIFTY AUTO S&P BSE AUTO a. To select securities from five major sectoral indices
listed in both NSE & BSE. 6 ADANITRANS NIFTY ENERGY S&P BSE POWER b. To estimate the beta coefficient value for each
securities by the time frame taken for study. 7 HINDPETRO NIFTY ENERGY S&P BSE ENERGY c. To calculate the coefficient of determination (R2) for the securities. 8 ONGC NIFTY ENERGY S&P BSE ENERGY d. To estimate the expected return for all selected securities using CAPM. 9 RELIANCE NIFTY ENERGY S&P BSE ENERGY e. To rank all the securities based on their CAPM expected return. 10 TATAPOWER NIFTY ENERGY S&P BSE POWER 3.4 LIMITATIONS OF THE STUDY: S&P BSE 11 CADILAHC NIFTY PHARMA Every research has its own limitations. The limitations of HEALTHCARE this study are: S&P BSE 12 CIPLA NIFTY PHARMA HEALTHCARE
164 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
S&P BSE HEROMOT NIFTY 13 DIVISLAB NIFTY PHARMA 3 0.86 0.90 HEALTHCARE OCO AUTO NIFTY 4 MARUTI 1.18 1.23 S&P BSE AUTO 14 DRREDDY NIFTY PHARMA HEALTHCARE NIFTY 5 MRF 0.78 0.68 AUTO S&P BSE ADANITRA NIFTY 15 LUPIN NIFTY PHARMA 6 0.49 0.64 HEALTHCARE NS ENERGY HINDPETR NIFTY 7 1.60 0.94 O ENERGY 16 COLPAL NIFTY FMCG S&P BSE FMCG NIFTY 8 ONGC 0.95 1.30 ENERGY NIFTY 17 HINDUNILVR NIFTY FMCG S&P BSE FMCG 9 RELIANCE 1.14 1.30 ENERGY TATAPOWE NIFTY 10 0.76 0.70 18 MARICO NIFTY FMCG S&P BSE FMCG R ENERGY NIFTY 11 CADILAHC PHARM 0.58 0.94 19 NESTLEIND NIFTY FMCG S&P BSE FMCG A NIFTY 12 CIPLA PHARM 0.69 0.98 20 PGHH NIFTY FMCG S&P BSE FMCG A NIFTY 13 DIVISLAB PHARM 0.65 0.91 21 AXISBANK NIFTY BANK S&P BSE BANKEX A NIFTY 14 DRREDDY PHARM 0.77 0.86 22 HDFCBANK NIFTY BANK S&P BSE BANKEX A NIFTY 15 LUPIN PHARM 0.95 0.86 23 ICICIBANK NIFTY BANK S&P BSE BANKEX A NIFTY 16 COLPAL 1.13 0.75 FMCG 24 KOTAKBANK NIFTY BANK S&P BSE BANKEX HINDUNILV NIFTY 17 0.79 1.16 R FMCG NIFTY 18 MARICO 1.06 0.75 25 SBIN NIFTY BANK S&P BSE BANKEX FMCG NIFTY 19 NESTLEIND 1.15 0.97 5. ESTIMATION OF BETA COEFFICIENT (β): FMCG NIFTY 20 PGHH 0.73 0.41 The beta coefficient (β) is obtained from the following FMCG NIFTY formula: 21 AXISBANK 1.16 1.33 BANK NIFTY Where, Beta coefficient (β) = 22 HDFCBANK 0.68 0.84 BANK
NIFTY 23 ICICIBANK 0.93 1.14 BANK KOTAKBAN NIFTY 24 0.63 0.88 Where, K BANK NIFTY i. R is the return on an individual stock - Dependent 25 SBIN 1.58 0.84 e BANK Variable. Table 5.2 comparison of beta value for securities listed ii. Rm is the return on the overall market - Independent Variable. in BSE: iii. Variance is the square of standard deviation and BETA (β) VALUE BETA (β) (1st November 2019 VALUE how far the market’s data points spread- S.n SYMBOL SECTOR to 31st January 2020) (1st February o out from their average value 2020 to 30th iv. Covariance is how changes in a stock’s returns are April 2020) BAJAJ- S&P BSE related to changes in the markets return and it is the 1 0.33 0.82 AUTO AUTO statistic that measures how two variables co-vary. S&P BSE 2 EXIDEIND 0.94 0.61 AUTO Table 5.1 comparison of beta value for securities listed HEROMOT S&P BSE 3 0.88 0.93 in NSE: OCO AUTO S&P BSE 4 MARUTI 1.20 1.25 BETA (β) VALUE BETA (β) AUTO st st S.n (1 November 2019 VALUE (1 S&P BSE SYMBOL SECTOR st 5 MRF 0.84 0.71 o to 31 January February 2020 to AUTO th 2020) 30 April 2020) ADANITRA S&P BSE 6 0.87 0.79 BAJAJ- NIFTY NS POWER 1 0.32 0.80 AUTO AUTO HINDPETR S&P BSE 7 0.96 0.62 NIFTY O ENERGY 2 EXIDEIND 0.95 0.62 AUTO
165 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
S&P BSE 8 ONGC 0.47 0.95 From the above table 5.1 we can also infer that after the ENERGY impact of COVID in Indian stock market there are only 6 S&P BSE 9 RELIANCE 1.20 1.15 ENERGY securities (AXISBANK, RELIANCE, ONGC, MARUTI, TATAPOW S&P BSE 10 1.15 0.86 HINDUNILVR, ICICIBANK) has a beta value of greater ER POWER S&P BSE than 1, which shows that these securities are more volatile 11 CADILAHC HEALTHC 0.80 1.06 in the market. Among these 25 securities there are 19 ARE securities which have a beta value less than 1, this S&P BSE 12 CIPLA HEALTHC 0.76 1.02 indicates that these 19 securities are less volatile than their ARE corresponding market. AXISBANK from Nifty bank has S&P BSE the highest beta value of 1.33 and PGHH from Nifty 13 DIVISLAB HEALTHC 0.75 0.99 ARE FMCG has the lowest beta value of 0.41. It seems that no S&P BSE individual sector has a weightage over the other sectors in 14 DRREDDY HEALTHC 0.97 0.94 ARE the market, however the banking sector & energy sectors S&P BSE has the higher risk while compared to other sectors in 15 LUPIN HEALTHC 1.16 0.88 NSE. ARE S&P BSE 16 COLPAL 1.02 0.76 From the above table 5.2 we can infer that before the FMCG HINDUNIL S&P BSE impact of COVID in Indian stock market there are 8 17 0.75 1.17 VR FMCG securities SBIN, RELIANCE, MARUTI, NESTLEIND, S&P BSE 18 MARICO 0.98 0.75 AXISBANK, LUPIN, TATAPOWER, COLPAL has a FMCG NESTLEIN S&P BSE beta value of greater than 1, which shows that these 19 1.16 0.97 D FMCG securities are more volatile in the market. Among these 25 S&P BSE 20 PGHH 0.73 0.40 securities there are 17 securities which have a beta value FMCG less than 1, this indicates that these 17 securities are less S&P BSE 21 AXISBANK 1.16 1.30 BANKEX volatile than their corresponding market. SBIN from S&P
HDFCBAN S&P BSE BSE Bankex has the highest beta value of 1.57 and 22 0.61 0.84 K BANKEX BAJAJ-AUTO from S&P BSE Auto has the lowest beta S&P BSE 23 ICICIBANK 1.00 1.13 value of 0.33 BANKEX KOTAKBA S&P BSE 24 0.70 0.89 From the above table 5.2 we can also infer that after the NK BANKEX S&P BSE impact of COVID in Indian stock market there are only 7 25 SBIN 1.57 0.81 BANKEX securities AXISBANK, MARUTI, HINDUNILVR, RELIANCE, ICICIBANK, CADILAHC, CIPLA has a INTERPRETATION: beta value of greater than 1, which shows that these A Beta Coefficient value of greater than 1.00 indicates that securities is more volatile in the market. Among these 25 the stock is highly volatile than the market, and Beta securities there are 18 securities which have a beta value Coefficient value of less than 1.00 is less volatile than the less than 1, this indicates that these 19 securities are less market. A beta Coefficient value of 1.5 means that a volatile than their corresponding market. AXISBANK stock's excess return is expected to move 1.5 times than from S&P BSE Bankex has the highest beta value of 1.30 the market excess returns. and PGHH from S&P BSE FMCG has the lowest beta value of 0.40. It seems that as like NSE no individual From the above table 5.1 we can infer that before the impact of COVID in Indian stock market there are only 2 sector has a weightage over the other sectors in the market, however the banking sector, & FMCG sectors has the securities (HINDPETRO & SBIN) have a beta value higher risk while compared to other sectors in BSE. greater than 1.5 which indicates that these 2 securities are expected to move 1.5 times than the market excess returns. 6. ESTIMATION R-SQUARED AND ADJUSTED R- There are 6 other securities (MARUTI, AXISBANK, SQUARED: NESTLEIND, RELIANCE, COLPAL, MARICO) has a R-squared is the factual proportion of how close the beta value of greater than 1, which shows that these information is to the fitted relapse line. It is otherwise securities are more volatile in the market. Among these 25 called the coefficient of assurance, or the coefficient of securities there are 17 securities which have a beta value numerous conclusions for different relapses. 100% shows less than1; this indicates that these 17 securities are less that the model clarifies all the fluctuation of the reaction volatile than their corresponding market. HINDPETRO information around its mean. So also the balanced R- from Nifty Energy has the highest beta value of 1.60 and squared is an altered variant of R-squared that has been BAJAJ-AUTO from Nifty Auto has the lowest beta value balanced for the quantity of indicators in the model. The of 0.32 balanced R-squared increments just if the new term improves the model more than would be normal by some
166 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020 coincidence. It diminishes when an indicator improves the R2 VALUE (%) R2 VALUE (1st November 2019 to (%) S.n model by not exactly expected by some coincidence. SYMBOL SECTOR 31st January 2020) (1st February o 2020 to 30th Table 6.1 comparison of variance in proportion of the April 2020) dependent variable to that of the independent variable BAJAJ- S&P BSE 1 11.68 65.13 (R2) value for securities listed in NSE: AUTO AUTO S&P BSE 2 2 EXIDEIND 32.21 48.24 R VALUE (% ) AUTO R2 VALUE (%) S.n (1st November SYMBOL SECTOR (1st February 2020 HEROMOT S&P BSE o 2019 to 31st 3 43.13 63.73 to 30th April 2020) OCO AUTO January 2020) S&P BSE BAJAJ- NIFTY 4 MARUTI 74.36 86.56 1 11.47 66.03 AUTO AUTO AUTO S&P BSE NIFTY 5 MRF 39.40 58.76 2 EXIDEIND 32.63 49.82 AUTO AUTO HEROMOT NIFTY ADANITRA S&P BSE 3 41.94 62.73 6 6.98 21.73 OCO AUTO NS POWER NIFTY HINDPETR S&P BSE 4 MARUTI 75.25 86.97 7 33.71 33.26 AUTO O ENERGY NIFTY S&P BSE 5 MRF 36.29 57.90 8 ONGC 12.64 48.65 AUTO ENERGY S&P BSE ADANITRA NIFTY 9 RELIANCE 91.82 97.37 6 2.62 22.24 ENERGY NS ENERGY TATAPOW S&P BSE HINDPETR NIFTY 10 37.06 34.85 7 59.19 50.26 ER POWER O ENERGY S&P BSE NIFTY 11 CADILAHC HEALTHC 14.63 48.00 8 ONGC 33.49 54.83 ENERGY ARE NIFTY S&P BSE 9 RELIANCE 51.06 81.73 ENERGY 12 CIPLA HEALTHC 19.06 59.06 ARE TATAPOWE NIFTY 10 19.26 37.82 R ENERGY S&P BSE 13 DIVISLAB HEALTHC 21.12 72.45 NIFTY ARE 11 CADILAHC PHARM 13.08 45.90 A S&P BSE 14 DRREDDY HEALTHC 29.83 63.03 NIFTY ARE 12 CIPLA PHARM 27.74 64.05 A S&P BSE 15 LUPIN HEALTHC 34.62 45.80 NIFTY ARE 13 DIVISLAB PHARM 27.87 73.05 S&P BSE A 16 COLPAL 22.58 66.64 FMCG NIFTY HINDUNIL S&P BSE 14 DRREDDY PHARM 33.50 64.45 17 30.59 79.11 A VR FMCG S&P BSE NIFTY 18 MARICO 19.90 62.32 FMCG 15 LUPIN PHARM 40.35 52.00 NESTLEIN S&P BSE A 19 40.65 69.34 NIFTY D FMCG 16 COLPAL 26.47 67.20 20 PGHH S&P BSE FMCG 21.12 25.96 FMCG HINDUNILV NIFTY 17 31.41 78.87 21 AXISBANK S&P BSE R FMCG 48.61 80.27 BANKEX NIFTY 18 MARICO 21.96 59.36 22 HDFCBAN S&P BSE FMCG 35.46 81.14 K BANKEX NIFTY 19 NESTLEIND 37.04 69.32 23 ICICIBANK S&P BSE FMCG 42.51 90.42 BANKEX NIFTY 20 PGHH 21.38 24.81 24 KOTAKBA S&P BSE FMCG 22.30 75.14 NK BANKEX NIFTY 21 AXISBANK 50.51 80.45 25 SBIN S&P BSE BANK 56.28 66.21 BANKEX NIFTY 22 HDFCBANK 42.90 81.72 BANK INTERPRETATION: NIFTY 23 ICICIBANK 38.01 90.09 2 BANK Coefficient of determination (R ) is to find the variance in KOTAKBAN NIFTY 24 18.72 72.70 proportion of dependent variable to that of independent K BANK NIFTY variable. This is the statistical tool which helps to 25 SBIN 59.01 68.05 BANK determine how the differences in one particular variable can be explained by the difference in the other variable, Table 6.2 comparison of variance in proportion of the making it simple it is used to explain how much variability dependent variable to that of the independent variable (R2) value for securities listed in BSE: of one particular factor can be caused by the another factor which is related to it.
167 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
From the above table 6.1 we can infer that before the securities in the market, it also further indicates that more impact of COVID in Indian stock market there are only 1 than 75% of the data fit the regression model. SBIN has a securities MARUTI have a strong coefficient of coefficient of determination value greater than 50% which determination value of 75.25% which is greater than 70% indicates that these have generally a moderate size effect. and the model is good in explaining the size effect among The following 11 securities AXISBANK, the other listed securities in the market, it also further HEROMOTOCO, ICICIBANK, NESTLEIND, MRF, indicates that more than 75% of the data fit the regression TATAPOWER, HDFCBANK, LUPIN, HINDPETRO, model. The following 4 securities HINDPETRO, SBIN, EXIDEIND, HINDUNILVR has a coefficient of RELIANCE, AXISBANK has a coefficient of determination value more than 30% which indicates that it determination value greater than 50% which indicates that has a weak or low size effect. The other 11 securities have these have generally a moderate size effect. HDFCBANK, coefficient of determination value less than 30% and it HEROMOTOCO LUPIN, ICICIBANK, NESTLEIND, have a very weak effect size. ADANITRANS from S&P MRF, DRREDDY, ONGC, EXIDEIND, HINDUNILVR BSE Power has the lowest value of 6.9% and RELIANCE has a coefficient of determination value more than 30% also from S&P BSE Power has the highest value of which indicates that it has a weak or low size effect. The 91.81%. other 10 securities have coefficient of determination value From the above table 6.2 we can infer that before the less than 30% and it have a very weak effect size. impact of COVID in Indian stock market there are 8 ADANITRANS from Nifty Energy has the lowest value of securities RELIANCE, ICICIBANK, MARUTI, 2.62 HDFCBANK, AXISBANK, HINDUNILVR, From the above table 6.1 we can infer that before the KOTAKBANK, DIVISLAB have a strong coefficient of impact of COVID in Indian stock market there are 8 determination value of greater than 70% and the model is securities ICICIBANK, MARUTI, RELIANCE, good in explaining the size effect among the other listed HDFCBANK, AXISBANK, HINDUNILVR, DIVISLAB, securities in the market, it also further indicates that more KOTAKBANK have a strong coefficient of determination than 70% of the data fit the regression model. The value of greater than 70% and the model is good in following 9 securities NESTLEIND, COLPAL, SBIN, explaining the size effect among the other listed securities BAJAJ-AUTO, HEROMOTOCO, DRREDDY, MARICO, in the market, it also further indicates that more than 70% CIPLA, MRF has a coefficient of determination value of the data fit the regression model. The following 12 greater than 50% which indicates that these have generally securities NESTLEIND, SBIN, COLPAL, BAJAJ-AUTO, a moderate size effect. ONGC, EXIDEIND, CADILAHC, DRREDDY, CIPLA, HEROMOTOCO, MARICO, MRF, LUPIN, TATAPOWER, HINDPETRO has a coefficient of ONGC, LUPIN, HINDPETRO has a coefficient of determination value more than 30% which indicates that it determination value greater than 50% which indicates that has a weak or low size effect. The other 2 securities have these have generally a moderate size effect. EXIDEIND, coefficient of determination value less than 30% and it CADILAHC, TATAPOWER has a coefficient of have very weak effect size. . ADANITRANS from S&P determination value more than 30% which indicates that it BSE Power has the lowest value of 21.72 % and has a weak or low size effect. The other 2 securities have RELIANCE also from S&P BSE Power has the highest coefficient of determination value less than 30% and it value of 97.36%. have very weak effect size. ADANITRANS from Nifty Energy has the lowest value of 22.2% and ICICIBANK 7. ESTIMATION OF CAPM: has the highest value of 90%. The expected return is obtained from individual securities From the above table 6.2 we can infer that before the from the following formula: impact of COVID in Indian stock market there are only 2 securities RELIANCE, MARUTI have a strong coefficient Ri = Rf + β * (Rm − Rf) of determination value of greater than 70% and the model Where, Beta coefficient (β) = is good in explaining the size effect among the other listed Table 7.1 shows the CAPM expected return for both NSE and BSE:
NSE BSE
S.no SYMBOL CAPM (% ) CAPM (% ) CAPM (%) CAPM (% ) (1st February (1st November 2019 (1st February (1st November 2019 to 31st January 2020) 2020 to 30th to 31st January 2020 to 30th April 2020) 2020) April 2020) 1 BAJAJ-AUTO 2.66 0.75 2.63 0.69
2 EXIDEIND 0.21 1.48 0.24 1.50 3 HEROMOTOCO 0.55 0.39 0.45 0.25
168 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
4 MARUTI -0.70 -0.88 -0.77 -0.98 5 MRF 0.85 1.22 0.60 1.12 6 ADANITRANS 1.99 1.40 0.51 0.81 7 HINDPETRO -2.36 0.25 0.17 1.47 8 ONGC 0.19 -1.15 2.08 0.18 9 RELIANCE -0.54 -1.17 -0.80 -0.58 10 TATAPOWER 0.92 1.14 -0.58 0.52 11 CADILAHC 1.66 0.24 0.79 -0.23 12 CIPLA 1.20 0.10 0.93 -0.09 13 DIVISLAB 1.36 0.34 0.97 0.03 14 DRREDDY 0.88 0.53 0.14 0.22 15 LUPIN 0.21 0.55 -0.61 0.45 16 COLPAL -0.52 0.98 -0.07 0.94 17 HINDUNILVR 0.83 -0.61 0.97 -0.66 18 MARICO -0.22 0.97 0.09 0.96 19 NESTLEIND -0.58 0.12 -0.64 0.12 20 PGHH 1.07 2.27 1.07 2.32 21 AXISBANK -0.64 -1.27 -0.64 -1.17 22 HDFCBANK 1.27 0.60 1.52 0.63 23 ICICIBANK 0.29 -0.55 0.01 -0.50 24 KOTAKBANK 1.44 0.44 1.18 0.43 25 SBIN -2.27 0.61 -2.20 0.73 ANALYSIS AND INTERPRETATION: Table 7.2 Showing results for Nifty Auto & S&P BSE Auto on the basis of CAPM expected return.
NSE BSE SYMBOL CAPM CAPM RANKING CAPM CAPM RANKING (before) (after) (current) (before) (after) (current) BAJAJ-AUTO 2.66 0.75 3 2.63 0.69 3 EXIDEIND 0.21 1.48 1 0.24 1.50 1 HEROMOTOCO 0.55 0.39 4 0.45 0.25 4 MARUTI -0.70 -0.88 5 -0.77 -0.98 5 MRF 0.85 1.22 2 0.60 1.12 2
NIFTY AUTO
3.00
2.50
2.00
1.50
1.00
CAPM 0.50
-
(0.50)
(1.00)
(1.50) BAJAJ-AUTO EXIDEIND HEROMOTOCO MARUTI MRF NSE (1st November 2019 to 31st January 2020) 2.66 0.21 0.55 (0.70) 0.85 NSE (1st February 2020 to 30th April 2020) 0.75 1.48 0.39 (0.88) 1.22
169 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
S&P BSE AUTO
3.00
2.50
2.00
1.50
1.00
CAPM 0.50
-
(0.50)
(1.00)
(1.50) BAJAJ-AUTO EXIDEIND HEROMOTOCO MARUTI MRF BSE (1st November 2019 to 31st January 2020) 2.63 0.24 0.45 (0.77) 0.60 BSE (1st February 2020 to 30th April 2020) 0.69 1.50 0.25 (0.98) 1.12
7.1 INTERPRETATION FROM AUTOMOBILE SECTOR:
The wheels of auto stock perforated as the impact of covid-19 disrupts its supplies, and the sales decline in automobile sector due to various phases of lockdown in India the sector seems to be accelerating in top gear while compared with other selected sectors from NSE & BSE. Meanwhile the sector has heavy loss and it is expected to recover in the coming months. From the above table 7.2 we can infer that EXIDEIND and MRF has performed well and from the selected securities only these 2 securities from both NSE & BSE have a growth pattern during the corona supremacy. The BAJAJ-AUTO has yielded a better return before the strike of pandemic but however it has huge decline as far as other securities. HEROMOTOCO having small decline and maintains a minimal fluctuation in the returns. MARUTI have outperformed in both NSE & BSE even before and after the impact of pandemic in the market.
Graphs showing returns for individual securities from both time-frames:
BAJAJ-AUTO
3.00
2.50
2.00
1.50 CAPM
1.00
0.50
- NSE BSE 1st November 2019 to 31st January 2020 2.66 2.63 1st February 2020 to 30th April 2020 0.75 0.69
170 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
EXIDEIND
1.60
1.40
1.20
1.00
0.80 CAPM 0.60
0.40
0.20
- NSE BSE 1st November 2019 to 31st January 2020 0.21 0.24 1st February 2020 to 30th April 2020 1.48 1.50
HEROMOTOCO
0.60
0.50
0.40
0.30 CAPM 0.20
0.10
- NSE BSE 1st November 2019 to 31st January 2020 0.55 0.45 1st February 2020 to 30th April 2020 0.39 0.25
MARUTI
(0.66)
(0.68)
(0.70)
(0.72) CAPM
(0.74)
(0.76)
(0.78) NSE BSE 1st November 2019 to 31st January 2020 (0.70) (0.77) 1st February 2020 to 30th April 2020 (0.70) (0.77)
171 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
MRF
1.40
1.20
1.00
0.80
CAPM 0.60
0.40
0.20
- NSE BSE 1st November 2019 to 31st January 2020 0.85 0.60 1st February 2020 to 30th April 2020 1.22 1.12
Table 7.3 Showing results for Nifty Energy & S&P BSE Energy, Power on the basis of CAPM expected return.
NSE BSE
SYMBOL CAPM CAPM RANKING CAPM CAPM RANKING (before) (after) (current) (before) (after) (current)
ADANITRANS 1.99 1.40 1 0.51 0.81 2
HINDPETRO -2.36 0.25 3 0.17 1.47 1 ONGC 0.19 -1.15 4 2.08 0.18 4 RELIANCE -0.54 -1.17 5 -0.80 -0.58 5 TATAPOWER 0.92 1.14 2 -0.58 0.52 3
NIFTY ENERGY
2.50
2.00
1.50
1.00
0.50
-
CAPM (0.50)
(1.00)
(1.50)
(2.00)
(2.50)
(3.00) ADANITRAN HINDPETRO ONGC RELIANCE TATAPOWER S NSE (1st November 2019 to 31st January 2020) 1.99 (2.36) 0.19 (0.54) 0.92 NSE (1st February 2020 to 30th April 2020) 1.40 0.25 (1.15) (1.17) 1.14
172 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
S&P BSE ENERGY, POWER
2.50
2.00
1.50
1.00
CAPM 0.50
-
(0.50)
(1.00) ADANITRANS HINDPETRO ONGC RELIANCE TATAPOWER BSE (1st November 2019 to 31st January 2020) 0.51 0.17 2.08 (0.80) (0.58) BSE (1st February 2020 to 30th April 2020) 0.81 1.47 0.18 (0.58) 0.52
7.2 INTERPRETATION FROM ENERGY SECTOR:
While the energy sector across the globe struggled in deep crisis, the oil prices crashes far down as not before in the history. This downfall may be because of the minimal demand for crude oil in the global market. The other factor which has to be considered in India is the uses of commercial electricity by the industrial sector have slashes down due to the lockdown and various restrictions by the government in order to stop the spread of novel corona virus. But however from table 7.3 we infer that the securities like ADANITRANS, TATAPOWER, & HINDPETRO from both NSE & BSE managed to streamed up with their performance which surprised the investor. By comparing all other securities HINDPETRO have a great fluctuation in terms of growth and ONGC by withering. Although RELIANCE have not surprised the investor as it has outperformed in both time-frames. Hope energy sector will be energized at earliest.
Graphs showing returns for individual securities from both time-frames:
ADANITRANS
2.50 2.00
1.50
CAPM 1.00 0.50 - NSE BSE 1st November 2019 to 31st January 2020 1.99 0.51 1st February 2020 to 30th April 2020 1.40 0.81
HINDPETRO
2.00 1.50 1.00 0.50 - (0.50)
CAPM (1.00) (1.50) (2.00) (2.50) (3.00) NSE BSE 1st November 2019 to 31st January 2020 (2.36) 0.17 1st February 2020 to 30th April 2020 0.25 1.47
173 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
ONGC
2.50
2.00
1.50
1.00
0.50 CAPM -
(0.50)
(1.00)
(1.50) NSE BSE 1st November 2019 to 31st January 2020 0.19 2.08 1st February 2020 to 30th April 2020 (1.15) 0.18
RELIANCE
-
(0.20)
(0.40)
(0.60)
CAPM (0.80)
(1.00)
(1.20)
(1.40) NSE BSE 1st November 2019 to 31st January 2020 (0.54) (0.80) 1st February 2020 to 30th April 2020 (1.17) (0.58)
TATAPOWER
1.40 1.20 1.00 0.80 0.60 0.40
CAPM 0.20 - (0.20) (0.40) (0.60) (0.80) NSE BSE 1st November 2019 to 31st January 2020 0.92 (0.58) 1st February 2020 to 30th April 2020 1.14 0.52
174 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
Table 7.4 Showing results for Nifty Pharma & S&P BSE Healthcare on the basis of CAPM expected return.
NSE BSE
SYMBOL CAPM CAPM RANKING CAPM CAPM RANKING (before) (after) (current) (before) (after) (current)
CADILAHC 1.66 0.24 4 0.79 -0.23 5
CIPLA 1.20 0.10 5 0.93 -0.09 4
DIVISLAB 1.36 0.34 3 0.97 0.03 3
DRREDDY 0.88 0.53 2 0.14 0.22 2
LUPIN 0.21 0.55 1 -0.61 0.45 1
NIFTY PHARMA
1.80
1.60
1.40
1.20
1.00
CAPM 0.80
0.60
0.40
0.20
- CADILAHC CIPLA DIVISLAB DRREDDY LUPIN NSE (1st November 2019 to 31st January 1.66 1.20 1.36 0.88 0.21 2020) NSE (1st February 2020 to 30th April 2020) 0.24 0.10 0.34 0.53 0.55
S&P BSE HEALTHCARE
1.20
1.00
0.80
0.60
0.40
0.20 CAPM -
(0.20)
(0.40)
(0.60)
(0.80) CADILAHC CIPLA DIVISLAB DRREDDY LUPIN BSE (1st November 2019 to 31st January 0.79 0.93 0.97 0.14 (0.61) 2020) BSE (1st February 2020 to 30th April 2020) (0.23) (0.09) 0.03 0.22 0.45
175 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
7.3 INTERPRETATION FROM PHARMA AND HEALTHCAE SECTOR:
Well this sector has its primary impact on covid-19 and directly deals with current scenario. The securities comprised in this sector are more expected by the investor to fetch high yield. Even though except few, many failed to do so in the past. However in the early lockdown stages the pharma securities were underperformed and created many turmoil’s among the investors, whether to buy or sell. In recent days this sector has a rapid growth pattern and fetches high yield on the go, as everyone expected a better return from this specific sector. From table 7.4 we can infer that LUPIN & DRREDDY justified the investor during the course of time. The pharma and healthcare sector are expected to recover rapidly and to top the table with profit as much earliest.
Graphs showing returns for individual securities from both time-frames:
CADILAHC
2.00
1.50
1.00
CAPM 0.50
-
(0.50) NSE BSE 1st November 2019 to 31st January 2020 1.66 0.79 1st February 2020 to 30th April 2020 0.24 (0.23)
CIPLA
1.40 1.20 1.00
0.80 0.60 CAPM 0.40 0.20 - (0.20) NSE BSE 1st November 2019 to 31st January 2020 1.20 0.93 1st February 2020 to 30th April 2020 0.10 (0.09)
DIVISLAB
1.60 1.40 1.20
1.00
0.80 CAPM 0.60 0.40 0.20 - NSE BSE 1st November 2019 to 31st January 2020 1.36 0.97 1st February 2020 to 30th April 2020 0.34 0.03
176 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
DRREDDY
1.00 0.90 0.80 0.70
0.60 0.50
CAPM 0.40 0.30 0.20 0.10 - NSE BSE 1st November 2019 to 31st January 2020 0.88 0.14 1st February 2020 to 30th April 2020 0.53 0.22
LUPIN
0.80 0.60 0.40
0.20 -
CAPM (0.20) (0.40) (0.60) (0.80) NSE BSE 1st November 2019 to 31st January 2020 0.21 (0.61) 1st February 2020 to 30th April 2020 0.55 0.45
Table 7.5 Showing results for Nifty FMCG & S&P BSE FMCG on the basis of CAPM expected return.
NSE BSE SYMBOL CAPM CAPM RANKING CAPM CAPM RANKING (before) (after) (current) (before) (after) (current)
COLPAL -0.52 0.98 2 -0.07 0.94 2
HINDUNILVR 0.83 -0.61 5 0.97 -0.66 5
MARICO -0.22 0.97 3 0.09 0.96 3
NESTLEIND -0.58 0.12 4 -0.64 0.12 4
PGHH 1.07 2.27 1 1.07 2.32 1
NIFTY FMCG
2.50 2.00
1.50
1.00
0.50 CAPM - (0.50) (1.00) HINDUNILV COLPAL MARICO NESTLEIND PGHH R NSE (1st November 2019 to 31st January (0.52) 0.83 (0.22) (0.58) 1.07 2020) NSE (1st February 2020 to 30th April 2020) 0.98 (0.61) 0.97 0.12 2.27
177 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
S&P BSE FMCG
2.50 2.00
1.50 1.00 0.50 CAPM - (0.50) (1.00) HINDUNILV COLPAL MARICO NESTLEIND PGHH R BSE (1st November 2019 to 31st January (0.07) 0.97 0.09 (0.64) 1.07 2020) BSE (1st February 2020 to 30th April 2020) 0.94 (0.66) 0.96 0.12 2.32
7.4 INTERPRETATION FROM FMCG SECTOR:
In the history of humanity we seen many disasters, but the challenges what we are facing now is somewhat different and the magnitude of this challenge is impenetrable. The FMCG sector is not like other sectors, inspite of covid-19 pandemic this sector had a high demand as they contribute to all our daily needs. The FMCG sector has performed quite well during pandemic period. The prevailing opportunities and demand are been seized by the FMCG sector as many companies have launched and also increased their sales in hygiene products such as liquid hand-wash, soap, sanitizers and disinfectants. From table 7.5 we can infer that securities like PGHH, MARICO, COLPAL & NESTLEIND had a better yield to their investors, many other securities listed under FMCG sector have throttled up their performance during the most difficult times.
Graphs showing returns for individual securities from both time-frames:
COLPAL
1.20 1.00 0.80
0.60
0.40
0.20 CAPM - (0.20) (0.40) (0.60) NSE BSE 1st November 2019 to 31st January 2020 (0.52) (0.07) 1st February 2020 to 30th April 2020 0.98 0.94
HINDUNILVR
1.20 1.00 0.80 0.60
0.40 0.20
CAPM - (0.20) (0.40) (0.60) (0.80) NSE BSE 1st November 2019 to 31st January 2020 0.83 0.97 1st February 2020 to 30th April 2020 (0.61) (0.66)
178 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
MARICO
1.20 1.00 0.80
0.60 0.40 CAPM 0.20 - (0.20) (0.40) NSE BSE 1st November 2019 to 31st January 2020 (0.22) 0.09 1st February 2020 to 30th April 2020 0.96 0.96
NESTLEIND
0.20 0.10 - (0.10) (0.20)
CAPM (0.30) (0.40) (0.50) (0.60) (0.70) NSE BSE 1st November 2019 to 31st January 2020 (0.58) (0.64) 1st February 2020 to 30th April 2020 0.12 0.12
PGHH
2.50
2.00
1.50
CAPM 1.00
0.50
- NSE BSE 1st November 2019 to 31st January 2020 1.07 1.07 1st February 2020 to 30th April 2020 2.27 2.32
Table 7.6 Showing results for Nifty Bank & S&P BSE Bankex on the basis of CAPM expected return.
NSE BSE SYMBOL CAPM CAPM RANKING CAPM CAPM RANKING (before) (after) (current) (before) (after) (current)
AXISBANK -0.64 -1.27 5 -0.64 -1.17 5
HDFCBANK 1.27 0.60 2 1.52 0.63 2
ICICIBANK 0.29 -0.55 4 0.01 -0.50 4 KOTAKBANK 1.44 0.44 3 1.18 0.43 3 SBIN -2.27 0.61 1 -2.20 0.73 1
179 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
NIFTY BANK
2.00 1.50 1.00
0.50 - (0.50) CAPM (1.00) (1.50) (2.00) (2.50) KOTAKBAN AXISBANK HDFCBANK ICICIBANK SBIN K NSE (1st November 2019 to 31st January (0.64) 1.27 0.29 1.44 (2.27) 2020) NSE (1st February 2020 to 30th April 2020) (1.27) 0.60 (0.55) 0.44 0.61
S&P BSE BANKEX
2.00 1.50 1.00 0.50 - (0.50)
CAPM (1.00) (1.50) (2.00) (2.50) KOTAKBAN AXISBANK HDFCBANK ICICIBANK SBIN K BSE (1st November 2019 to 31st January (0.64) 1.52 0.01 1.18 (2.20) 2020) BSE (1st February 2020 to 30th April 2020) (1.17) 0.63 (0.50) 0.43 0.73
7.5 INTERPRETATION FROM BANKING SECTOR:
Banks are the foundation for any economy and have a direct impact during any financial crisis. Banking stocks are yet to be fully priced, in the meantime it has a severe impact on pandemic and affected a lot. Retrieving of banking sectors from the supremacy of corona is still awaited. There are baskets of selective securities have performed well during the hit of covid-19 waves in India. This downfall might be because of the challenges which they are facing in recovery of loans for the past few months and this exemption is further extended to the end of August, however some moratorium given by RBI as a corrective measure to regulate this sectors during the corona outbreak. Apart from this we have to notice that insurance companies have great scope to emerge in the market. While choosing banking stocks, one should look for a combo of high provision coverage, strong capital ratios & deep funding. From table7.6 we can infer that only SBIN has performed well than all other selected securities. SBIN is the only public sector bank which is been selected by the author from banking sector and the rest are private sector bank. HDFCBANK & KOTAKBANK have somewhat managed, while AXISBANK & ICICIBANK have faced a huge decline.
Graphs showing returns for individual securities from both time-frames:
AXISBANK
-
(0.20)
(0.40)
(0.60)
CAPM (0.80)
(1.00)
(1.20)
(1.40) NSE BSE 1st November 2019 to 31st January 2020 (0.64) (0.64) 1st February 2020 to 30th April 2020 (1.27) (1.17)
180 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
HDFCBANK
1.60
1.40
1.20
1.00
0.80 CAPM 0.60
0.40
0.20
- NSE BSE 1st November 2019 to 31st January 2020 1.27 1.52 1st February 2020 to 30th April 2020 0.60 0.63
ICICIBANK
0.40 0.30 0.20 0.10
-
(0.10) CAPM (0.20) (0.30) (0.40) (0.50) (0.60) NSE BSE 1st November 2019 to 31st January 2020 0.29 0.01 1st February 2020 to 30th April 2020 (0.55) (0.50)
KOTAKBANK
1.60
1.40
1.20
1.00
0.80 CAPM 0.60
0.40
0.20
- NSE BSE 1st November 2019 to 31st January 2020 1.44 1.18 1st February 2020 to 30th April 2020 0.44 0.43
181 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
SBIN
1.00
0.50
-
(0.50)
CAPM (1.00)
(1.50)
(2.00)
(2.50) NSE BSE 1st November 2019 to 31st January 2020 (2.27) (2.20) 1st February 2020 to 30th April 2020 0.61 0.73
8. CONCLUSION The covid-19 had a greater impact on stock market across the World, many investors in India really had a tough time and hope the comeback to normal as soon as possible. From all the above data we can see that from the selected sectors, only FMCG, Pharma & Healthcare have performed well during covid-19 outbreak and seems to be bullish. After many years of underperformance the Pharma shares had a great comeback and set the market on fire. Pharma has a good exposure in Indian stock market which helps the investors who have invested in this sector to feel safe and would be a better hiding place for them. We can also infer that the fluctuations are more or less same for securities listed in both NSE & BSE. Apart from the selected sectors, Telecom sector performs well and market is towards a bullish market, as the competition shrinks in their respective market. Investors whose portfolio comprised of FMCG sector, Pharma sector and Telecom sector might be luckier for the investment, which they made on these sectors as these particular markets have yielded high returns to them. Investors who would like to do changes in their portfolio can add some bunches of selected securities from the above sectors. It is better to avoid banking sector at this moment, as their recovery seems to be slow at current market scenario. Not all securities from banking sector are under performing, some perform well. The big deal here is that selecting right securities matters a lot here. Investors who wish to invest in banking sector can refer to the past down cycles to ensure that how some companies managed to overcome during the previous financial crisis over years. TABLE 8.1 SHOWING OVERALL EXPECTED RETURN FOR SELECTED SECURITIES:
NSE BSE S.no CAPM CAPM CAPM CAPM SYMBOL SYMBOL (before) (after) (before) (after) 1 PGHH 1.07 2.27 PGHH 1.07 2.32 2 EXIDEIND 0.21 1.48 EXIDEIND 0.24 1.50 3 ADANITRANS 1.99 1.40 HINDPETRO 0.17 1.47 4 MRF 0.85 1.22 MRF 0.60 1.12 5 TATAPOWER 0.92 1.14 MARICO 0.09 0.96 6 COLPAL -0.52 0.98 COLPAL -0.07 0.94 7 MARICO -0.22 0.97 ADANITRANS 0.51 0.81 8 BAJAJ-AUTO 2.66 0.75 SBIN -2.20 0.73 9 SBIN -2.27 0.61 BAJAJ-AUTO 2.63 0.69 10 HDFCBANK 1.27 0.60 HDFCBANK 1.52 0.63 11 LUPIN 0.21 0.55 TATAPOWER -0.58 0.52 12 DRREDDY 0.88 0.53 LUPIN -0.61 0.45
182 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved. International Journal for Research in Engineering Application & Management (IJREAM) ISSN : 2454-9150 Vol-06, Issue-04, July 2020
13 KOTAKBANK 1.44 0.44 KOTAKBANK 1.18 0.43 14 HEROMOTOCO 0.55 0.39 HEROMOTOCO 0.45 0.25 15 DIVISLAB 1.36 0.34 DRREDDY 0.14 0.22 16 HINDPETRO -2.36 0.25 ONGC 2.08 0.18 17 CADILAHC 1.66 0.24 NESTLEIND -0.64 0.12 18 NESTLEIND -0.58 0.12 DIVISLAB 0.97 0.03 19 CIPLA 1.20 0.10 CIPLA 0.93 -0.09 20 ICICIBANK 0.29 -0.55 CADILAHC 0.79 -0.23 21 HINDUNILVR 0.83 -0.61 ICICIBANK 0.01 -0.50 22 MARUTI -0.70 -0.88 RELIANCE -0.80 -0.58 23 ONGC 0.19 -1.15 HINDUNILVR 0.97 -0.66 24 RELIANCE -0.54 -1.17 MARUTI -0.77 -0.98 25 AXISBANK -0.64 -1.27 AXISBANK -0.64 -1.17
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183 | IJREAMV06I0464099 DOI : 10.35291/2454-9150.2020.0519 © 2020, IJREAM All Rights Reserved.